Stochastic Geometry Analysis of a New GSCM with Dual Visibility Regions

TL;DR

This paper introduces a novel geometry-based stochastic channel model with dual visibility regions for scatterers, capturing realistic multipath propagation characteristics and their dependence on scatterer heights and positions.

Contribution

It proposes a new GSCM with dual disk visibility regions for scatterers, incorporating height-dependent visibility and probabilistic noncontiguous VRs, derived using stochastic geometry.

Findings

Derived PMF of the number of MPCs

Obtained distance distributions and ToA statistics

Model closely emulates COST-259 propagation characteristics

Abstract

The geometry-based stochastic channel models (GSCM), which can describe realistic channel impulse responses, often rely on the existence of both {\em local} and {\em far} scatterers. However, their visibility from both the base station (BS) and mobile station (MS) depends on their relative heights and positions. For example, the condition of visibility of a scatterer from the perspective of a BS is different from that of an MS and depends on the height of the scatterer. To capture this, we propose a novel GSCM where each scatterer has dual disk visibility regions (VRs) centered on itself for both BS and MS, with their radii being our model parameters. Our model consists of {\em short} and {\em tall} scatterers, which are both modeled using independent inhomogeneous Poisson point processes (IPPPs) having distinct dual VRs. We also introduce a probability parameter to account for the varying visibility of tall scatterers from different MSs, effectively emulating their noncontiguous VRs. Using stochastic geometry, we derive the probability mass function (PMF) of the number of multipath components (MPCs), the marginal and joint distance distributions for an active scatterer, the mean time of arrival (ToA), and the mean received power through non-line-of-sight (NLoS) paths for our proposed model. By selecting appropriate model parameters, the propagation characteristics of our GSCM are demonstrated to closely emulate those of the COST-259 model.